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dc.contributor.authorLivingstone, Mark
dc.contributor.authorFolkman, Lukas
dc.contributor.authorYang, Yuedong
dc.contributor.authorZhang, Ping
dc.contributor.authorMort, Matthew
dc.contributor.authorCooper, David N
dc.contributor.authorLiu, Yunlong
dc.contributor.authorStantic, Bela
dc.contributor.authorZhou, Yaoqi
dc.date.accessioned2018-01-24T12:30:29Z
dc.date.available2018-01-24T12:30:29Z
dc.date.issued2017
dc.identifier.issn1059-7794
dc.identifier.doi10.1002/humu.23283
dc.identifier.urihttp://hdl.handle.net/10072/352664
dc.description.abstractSynonymous single-nucleotide variants (SNVs), although they do not alter the encoded protein sequences, have been implicated in many genetic diseases. Experimental studies indicate that synonymous SNVs can lead to changes in the secondary and tertiary structures of DNA and RNA, thereby affecting translational efficiency, cotranslational protein folding as well as the binding of DNA-/RNA-binding proteins. However, the importance of these various features in disease phenotypes is not clearly understood. Here, we have built a support vector machine (SVM) model (termed DDIG-SN) as a means to discriminate disease-causing synonymous variants. The model was trained and evaluated on nearly 900 disease-causing variants. The method achieves robust performance with the area under the receiver operating characteristic curve of 0.84 and 0.85 for protein-stratified 10-fold cross-validation and independent testing, respectively. We were able to show that the disease-causing effects in the immediate proximity to exon–intron junctions (1–3 bp) are driven by the loss of splicing motif strength, whereas the gain of splicing motif strength is the primary cause in regions further away from the splice site (4–69 bp). The method is available as a part of the DDIG server at http://sparks-lab.org/ddig.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherJohn Wiley & Sons
dc.relation.ispartofpagefrom1336
dc.relation.ispartofpageto1347
dc.relation.ispartofissue10
dc.relation.ispartofjournalHuman Mutation
dc.relation.ispartofvolume38
dc.subject.fieldofresearchGenetics
dc.subject.fieldofresearchGenetics not elsewhere classified
dc.subject.fieldofresearchClinical sciences
dc.subject.fieldofresearchcode3105
dc.subject.fieldofresearchcode310599
dc.subject.fieldofresearchcode3202
dc.titleInvestigating DNA-, RNA-, and protein-based features as a means to discriminate pathogenic synonymous variants
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.hasfulltextNo Full Text
gro.griffith.authorStantic, Bela
gro.griffith.authorFolkman, Lukas
gro.griffith.authorZhang, Ping


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